A simultaneous electroencephalography and eye-tracking dataset in elite athletes during alertness and concentration tasks

The dataset of simultaneous 64-channel electroencephalography (EEG) and high-speed eye-tracking (ET) recordings was collected from 31 professional athletes and 43 college students during alertness behavior task (ABT) and concentration cognitive task (CCT). The CCT experiment lasting 1–2 hours included five sessions for groups of the Shooting, Archery and Modern Pentathlon elite athletes and the controls. Concentration targets included shooting target and combination target with or without 24 different directions of visual distractors and 2 types of music distractors. Meditation and Schulte Grid trainings were done as interventions. Analysis of the dataset aimed to extract effective biological markers of eye movement and EEG that can assess the concentration level of talented athletes compared with same-aged controls. Moreover, this dataset is useful for the research of related visual brain-computer interfaces.


1
The explanation of ET data validation 1/6 SFig.1 Examples of data in the alertness task with high and low valid data proportion 2/6 SFig.2 Examples of low and high inter-sample distance of data in the alertness task 3/6 SFig.

The explanation of ET data validation
In general, good data should have low data loss rate, low noise level, and show that the participant was actively following task instructions.
Here we give some examples of how data of different quality look like. The participant index, task name and value of data quality measures are shown in the title of figures. Note that the data quality values displayed in figure titles are calculated from the entire data of the participant in this task, not from the displayed period. In the Alertness (ABT) task the participants' eyes were usually tracking the move dot on the circle, so the gaze data had a sinusoidal shape. In the rest of tasks, the participants' eyes should always fixate at the screen center.
(1) Proportion of valid data (denoted as p(valid)) (SFig.1) (2) Inter-sample distance (SFig. 2) The gaze data in SFig.2b looked "thicker" compared to the data in SFig.2a due to the presence of high-frequency noise. This suggested that tracking of the pupil or corneal reflection point was noisy during this period of the experiment. Note that blinks were excluded when calculating inter-sample distance.
(3) Distance to screen center (SFig. 3) The participant in SFig.3a was fixating very accurately at the screen center. The participant in SFig.3b fixated away from the fixation point at the screen center for four times (around 177-187, 193-197, 205-206, and 210-217 seconds) in the figure. This suggested that the participant was not fully concentrated on the experiment during this period.

SFig. 2
Examples of low (a) and high (b) inter-sample distance of data in the alertness task. The limits and scales of the y-axis of the two panels are the same. The inter-sample distance was calculated only in valid data (blinks were excluded). If binocular data were presented it was first calculated for each eye and then averaged together. Note that the value of mean inter-sample distance in figure titles are calculated from the entire data of the participant in this task, not from the displayed period. L/R-X: left/right horizontal gaze position; L/R-Y: left/right vertical gaze position.

SFig. 3
Examples of low (a) and high (b) distance to screen center in eye-open resting state data. The red lines represent the horizontal and vertical position of the screen center (1280 and 720 pixels, respectively) that the participant should fixate. The black lines are the recorded gaze data. The distance to screen center was calculated only in valid data (blinks were excluded). Note that the value of mean distance to center in figure titles are calculated from the entire data of the participant in this task, not from the displayed period. L-X: left horizontal gaze position; L-Y: left vertical gaze position.
The noise remaining in the data was primarily high frequency noise due to unreliable tracking, and jerks in gaze data probability due to partial blinks (blinks without the eyelids being completely closed, so the pupil could still be tracked but its center were deviated). The example of high-frequency noise was provided in SFig.2b and the example of partial blinks was provided in SFig.4.

EEG acquisition process
The EEG acquisition process had 4 steps.
(1). Equipment debugging. Before placing the EEG cap, we would switch on the equipment and debug the instrument to ensure smooth recording.
(2). Preparation before collection, including informing the subjects of hair washing in advance, the purpose of EEG collection and the non-harm of the collection process to relieve the tension of the subjects.
(3). Place EEG cap and connect VEOU/VEOL (vertical eyeball, left eye)，HEOR/HEOL (horizontal eyeball) and bilateral mastoid process (M1/M2) electrode in accordance with international standards. Wipe scalp with an appropriate amount of conductive cream or abrasive cream to reduce the impedance to less than 10 kΩ as far as possible, so as to reduce the influence of oil and cutin.
(4). Event markers in the recording process were used to mark the electrode dropping and the state of the subject in the recording process for subsequent processing.